How would you test a bike delivery option?

## Case: Launch a bike-delivery option You work on a **food delivery** marketplace (customers place orders; couriers deliver). The team is considering launching a **bike courier** delivery option in a dense urban area. ### 1) Why consider bikes? Explain the product/business rationale for adding bike couriers (vs only cars/scooters), including when bikes are likely to help and when they may hurt. ### 2) What should you consider when designing the experiment? List key factors/risks to account for when running an experiment for bike delivery, such as: - Marketplace dynamics (courier supply, demand, matching) - Interference/spillovers (violations of SUTVA) - Seasonality and external factors (e.g., weather) - Operational constraints (training, dispatch rules) - Data quality and logging ### 3) What metrics would you use? Propose a metric framework with: - **Primary success metric** (one main decision metric) - **Guardrails** (safety/quality/cost) - **Diagnostic metrics** (to understand mechanisms) Be explicit about definitions (e.g., what counts as “on-time”, how to treat cancellations, which time window). ### 4) What experimentation type would you choose? Recommend an experimentation approach and unit of randomization, and justify your choice. Options may include: - Classic A/B at order or user level - Courier-level randomization - Geo-based test (zone/city) - Time-based switchback / interleaving Include how you would handle bias/confounding, estimate sample size/MDE at a high level, and how you would ramp/monitor the launch.